Instructions to use hf-internal-testing/tiny-random-CLIPForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CLIPForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-CLIPForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-CLIPForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-CLIPForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-CLIPForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 90.1 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-CLIPForImageClassification/resolve/refs%2Fpr%2F38/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-CLIPForImageClassification@refs/pr/38/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-CLIPForImageClassification/resolve/refs%2Fpr%2F38/model.safetensors
90.1 kB
- Xet hash:
- 770df625e1ca29e0576dea38b18e7bf8b0f6ed95ef67a944f5f50d5537cfa6c6
- Size of remote file:
- 90.1 kB
- SHA256:
- d1b047ab0e59e5cedead127aa8d8e74524c1a3651d0ab8900fe192bc29318571
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